In the Proportional-Integral-Derivative (PID) controllers the control signal is a linear function
of: the current control error (the proportional part), the past errors (the integral part) and the …

This monograph systematically presents the existing identification methods of nonlinear
systems using the block-oriented approach It surveys various known approaches to the …

Olefins production plants are large-scale plants, in most of which gaseous and liquid
hydrocarbons are cracked to produce light olefins. The complex and large-scale nature of …

Wiener model identification and predictive control of a pH neutralisation process is
presented. Input-output data from a nonlinear, first principles simulation model of the pH …

We use Koopman theory to develop a data-driven nonlinear model reduction and
identification strategy for multiple-input multiple-output (MIMO) input-affine dynamical …

In this paper, new noniterative algorithms for the identification of (multivariable) block-
oriented nonlinear models consisting of the interconnection of linear time invariant systems …

In this paper, Laguerre filters and simple polynomials are used respectively as linear and
nonlinear parts of a Wiener structure. The obtained model structure is the so-called Wiener …

Nonlinearities are ubiquitous and often incur twofold influence, which could be a source of
troubles bringing uncertainty, inaccuracy, instability or even disaster in practice, and might …

This paper describes three nonlinear Model Predictive Control (MPC) algorithms for neural
Wiener models. In all algorithms the model or the output trajectory is linearised on-line and …

In this paper, a nonlinear model predictive control (NMPC) based on a piecewise linear
Wiener model is applied to a polymerization reactor. The static nonlinear part of the applied …